Epidemiology of stroke after cardiac surgery in the current era

Ani C Anyanwu1, Farzan Filsoufi, Sacha P Salzberg

  • 1Department of Cardiothoracic Surgery, Mount Sinai Medical Center, New York, NY, USA.

Insights

Stroke incidence after diverse cardiac surgery is low at 2.6%. A logistic model identifies 10 preoperative predictors, aiding in patient selection and stroke prevention research.

Area of Science:

  • Cardiology
  • Neurosurgery
  • Public Health

Background:

  • Previous stroke epidemiology studies focused on coronary bypass surgery, limiting applicability to diverse contemporary cardiac surgery populations.
  • Understanding stroke risk in varied cardiac surgical procedures is crucial for modern patient care.

Purpose of the Study:

  • To examine the epidemiology of stroke in a contemporary, heterogeneous cardiac surgery population.
  • To identify preoperative predictors of stroke after cardiac surgery.
  • To develop a predictive model for stroke risk in cardiac surgery patients.

Main Methods:

  • Retrospective analysis of a prospective database of 5085 adult patients undergoing various cardiac surgeries between 1998-2004.
  • Analysis included coronary bypass, isolated valve, valve/coronary bypass, thoracic aorta, transplant/assist device, and adult congenital procedures.
  • Multivariate logistic regression identified preoperative stroke predictors.

Main Results:

  • Overall stroke incidence was 2.6% (134 patients), with variations by procedure (e.g., 1.7% for coronary bypass, 4.6% for ascending aorta).
  • Stroke patients had significantly higher perioperative mortality (32.8% vs 4.9%) and longer hospitalizations (30 vs 7 days).
  • Ten preoperative predictors were identified: gender, age, aortic surgery, prior stroke, critical state, poor ventricular function, diabetes, peripheral vascular disease, unstable angina, and pulmonary hypertension.

Conclusions:

  • A relatively low stroke incidence was observed in a diverse contemporary cardiac surgical cohort.
  • A developed logistic model can identify high-risk patients preoperatively.
  • The model aids in improving patient counseling, selection, and defining cohorts for stroke prevention research.
Abstract

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